Search

OBJECTIVE: Pain and traumatic stress symptoms often co-occur. Evidence suggests that the neuropeptide oxytocine and pro-inflammatory cytokines are associated with both stress and pain. The aim of this pilot study was to explore relations between self-reported pain and traumatic stress, oxytocin and three cytokines in burn wounds.METHODS: An observational study in three burn centres was performed. Patients were invited to participate in the study when deep dermal injury was suspected. Patients completed the Impact of Event Scale (IES), a self-report questionnaire assessing traumatic stress symptoms, and they rated their pain the day prior to surgery. During surgery, eschar (i.e., burned tissue) was collected and stored at -80 ° C until analysis. When the data collection was complete, oxytocin and cytokine levels were analysed.RESULTS: Eschar from 53 patients was collected. Pain and stress scores were available from 42 and 36 patients respectively. Spearman correlational analyses showed an association between lower oxytocin levels at wound site and a higher total IES score (r = -0.37) and pain (r = -0.32). Mann-Whitney U tests comparing groups scoring high or low on pain or stress confirmed these associations.CONCLUSION: These analyses lend support to a hormonal pathway that may explain how psychological distress affects pain at skin level in patients with traumatic stress symptoms.

Oxidative potential (OP) has been suggested as a health-relevant measure of air pollution. Little information is available about OP spatial variation and the possibility to model its spatial variability. Our aim was to measure the spatial variation of OP within and between 10 European study areas. The second aim was to develop land use regression (LUR) models to explain the measured spatial variation. OP was determined with the dithiothreitol (DTT) assay in ten European study areas. DTT of PM2.5 was measured at 16–40 sites per study area, divided over street, urban and regional background sites. Three two-week samples were taken per site in a one-year period in three different seasons. We developed study-area specific LUR models and a LUR model for all study areas combined to explain the spatial variation of OP. Significant contrasts between study areas in OP were found. OP DTT levels were highest in southern Europe. DTT levels at street sites were on average 1.10 times higher than at urban background locations. In 5 of the 10 study areas LUR models could be developed with a median R2 of 33%. A combined study area model explained 30% of the measured spatial variability. Overall, LUR models did not explain spatial variation well, possibly due to low levels of OP DTT and a lack of specific predictor variables. © 2016 Elsevier Ltd

Background: Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. Methods: We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. Results: The 245,782 cohort members contributed 3,229,220person-years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01-1.53 per 5 ng/m3), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m3), PM10 S (1.58; 1.03-2.44 per 200 ng/m3), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m3) and PM10 K (1.17; 1.02-1.33 per 100 ng/m3). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. Conclusions: This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important. © 2015 Elsevier Ltd.

Item does not contain fulltext BACKGROUND: Patients with clinical N1 (cN1) lung cancer based on imaging are at risk for malignant mediastinal nodal involvement (N2 disease). Endosonography with a needle technique is suggested over surgical staging as a best first test for preoperative invasive mediastinal staging. The addition of a confirmatory mediastinoscopy seems questionable in patients with a normal mediastinum on imaging. This prospective multicenter trial investigated the sensitivity of preoperative linear endosonography and mediastinoscopy for mediastinal nodal staging of cN1 lung cancer. METHODS: Consecutive patients with operable and resectable cN1 non-small cell lung cancer underwent a lobe-specific mediastinal nodal staging by endosonography. The primary study outcome was sensitivity to detect N2 disease. The secondary end points were the prevalence of N2 disease, the negative predictive value (NPV) of both endosonography and endosonography with confirmatory mediastinoscopy, and the number of patients needed to detect one additional N2 disease with mediastinoscopy. RESULTS: Of the 100 patients with cN1 on imaging, 24 patients were diagnosed with N2 disease. Invasive mediastinal nodal staging with endosonography alone has a sensitivity of 38%, which can be increased to 73% by adding a mediastinoscopy. NPV was 81% and 91%, respectively. Ten mediastinoscopies are needed to detect one additional N2 disease missed by endosonography. CONCLUSIONS: Endosonography alone has an unsatisfactory sensitivity to detect mediastinal nodal metastasis in cN1 lung cancer, and the addition of a confirmatory mediastinoscopy is of added value. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT01456429; URL: www.clinicaltrials.gov.

Background: Studies have shown associations between mortality and long-term exposure to particulate matter air pollution. Few cohort studies have estimated the effects of the elemental composition of particulate matter on mortality. oBjectives: Our aim was to study the association between natural-cause mortality and long-term exposure to elemental components of particulate matter. Methods: Mortality and confounder data from 19 European cohort studies were used. Residential exposure to eight a priori–selected components of particulate matter (PM) was characterized following a strictly standardized protocol. Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc within PM size fractions ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) were estimated using land-use regression models. Cohort-specific statistical analyses of the associations between mortality and air pollution were conducted using Cox proportional hazards models using a common protocol followed by meta-analysis. results: The total study population consisted of 291,816 participants, of whom 25,466 died from a natural cause during follow-up (average time of follow-up, 14.3 years). Hazard ratios were positive for almost all elements and statistically significant for PM2.5 sulfur (1.14; 95% CI: 1.06, 1.23 per 200 ng/m3). In a two-pollutant model, the association with PM2.5 sulfur was robust to adjustment for PM2.5 mass, whereas the association with PM2.5 mass was reduced. conclusions: Long-term exposure to PM2.5 sulfur was associated with natural-cause mortality. This association was robust to adjustment for other pollutants and PM2.5. © 2015, Public Health Services, US Dept of Health and Human Services. All rights reserved.

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements.We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning.PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10.Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM. © 2015 Elsevier Ltd.